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Alkhabbas, F., Alawadi, S., Ayyad, M., Spalazzese, R. & Davidsson, P. (2023). ART4FL: An Agent-Based Architectural Approach for Trustworthy Federated Learning in the IoT. In: 2023 Eighth International Conference on Fog and Mobile Edge Computing (FMEC): . Paper presented at 2023 Eighth International Conference on Fog and Mobile Edge Computing (FMEC), Tartu, Estonia, 18-20 September 2023. Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>ART4FL: An Agent-Based Architectural Approach for Trustworthy Federated Learning in the IoT
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2023 (English)In: 2023 Eighth International Conference on Fog and Mobile Edge Computing (FMEC), Institute of Electrical and Electronics Engineers (IEEE), 2023Conference paper, Published paper (Refereed)
Abstract [en]

The integration of the Internet of Things (IoT) and Machine Learning (ML) technologies has opened up for the development of novel types of systems and services. Federated Learning (FL) has enabled the systems to collaboratively train their ML models while preserving the privacy of the data collected by their IoT devices and objects. Several FL frameworks have been developed, however, they do not enable FL in open, distributed, and heterogeneous IoT environments. Specifically, they do not support systems that collect similar data to dynamically discover each other, communicate, and negotiate about the training terms (e.g., accuracy, communication latency, and cost). Towards bridging this gap, we propose ART4FL, an end-to-end framework that enables FL in open IoT settings. The framework enables systems' users to configure agents that participate in FL on their behalf. Those agents negotiate and make commitments (i.e., contractual agreements) to dynamically form federations. To perform FL, the framework deploys the needed services dynamically, monitors the training rounds, and calculates agents' trust scores based on the established commitments. ART4FL exploits a blockchain network to maintain the trust scores, and it provides those scores to negotiating agents' during the federations' formation phase.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023
National Category
Computer Systems
Identifiers
urn:nbn:se:mau:diva-63749 (URN)10.1109/fmec59375.2023.10306036 (DOI)001103180200036 ()2-s2.0-85179515213 (Scopus ID)979-8-3503-1697-1 (ISBN)979-8-3503-1698-8 (ISBN)
Conference
2023 Eighth International Conference on Fog and Mobile Edge Computing (FMEC), Tartu, Estonia, 18-20 September 2023
Available from: 2023-11-20 Created: 2023-11-20 Last updated: 2023-12-28Bibliographically approved
Spalazzese, R., De Sanctis, M., Alkhabbas, F. & Davidsson, P. (2023). Shaping IoT Systems Together: The User-System Mixed-Initiative Paradigm and Its Challenges. In: Bedir Tekinerdogan, Catia Trubiani, Chouki Tibermacine, Patrizia Scandurra, Carlos E. Cuesta (Ed.), Software Architecture: 17th European Conference, ECSA 2023, Istanbul, Turkey, September 18–22, 2023, Proceedings. Paper presented at 17th European Conference, ECSA 2023, Istanbul, Turkey, September 18–22, 2023 (pp. 221-229). Springer
Open this publication in new window or tab >>Shaping IoT Systems Together: The User-System Mixed-Initiative Paradigm and Its Challenges
2023 (English)In: Software Architecture: 17th European Conference, ECSA 2023, Istanbul, Turkey, September 18–22, 2023, Proceedings / [ed] Bedir Tekinerdogan, Catia Trubiani, Chouki Tibermacine, Patrizia Scandurra, Carlos E. Cuesta, Springer, 2023, p. 221-229Conference paper, Published paper (Refereed)
Abstract [en]

Internet of Things (IoT) systems are often complex and have to deal with many challenges at the same time, both from a human and technical perspective. In this vision paper, we (i) describe IoT-Together , the Mixed-initiative Paradigm that we devise for IoT user-system collaboration and (ii) critically analyze related architectural challenges.

Place, publisher, year, edition, pages
Springer, 2023
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 14212
Keywords
Mixed-initiative paradigm, User-System Collaboration, Intelligent IoT Systems, Novel Experiences, Goal-driven IoT Systems
National Category
Computer Sciences
Identifiers
urn:nbn:se:mau:diva-64271 (URN)10.1007/978-3-031-42592-9_15 (DOI)2-s2.0-85172136763 (Scopus ID)978-3-031-42591-2 (ISBN)978-3-031-42592-9 (ISBN)
Conference
17th European Conference, ECSA 2023, Istanbul, Turkey, September 18–22, 2023
Available from: 2023-12-12 Created: 2023-12-12 Last updated: 2023-12-12Bibliographically approved
Alkhabbas, F., Alsadi, M., Alawadi, S., Awaysheh, F. M., Kebande, V. R. & Moghaddam, M. T. (2022). ASSERT: A Blockchain-Based Architectural Approach for Engineering Secure Self-Adaptive IoT Systems.. Sensors, 22(18), Article ID 6842.
Open this publication in new window or tab >>ASSERT: A Blockchain-Based Architectural Approach for Engineering Secure Self-Adaptive IoT Systems.
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2022 (English)In: Sensors, E-ISSN 1424-8220, Vol. 22, no 18, article id 6842Article in journal (Refereed) Published
Abstract [en]

Internet of Things (IoT) systems are complex systems that can manage mission-critical, costly operations or the collection, storage, and processing of sensitive data. Therefore, security represents a primary concern that should be considered when engineering IoT systems. Additionally, several challenges need to be addressed, including the following ones. IoT systems' environments are dynamic and uncertain. For instance, IoT devices can be mobile or might run out of batteries, so they can become suddenly unavailable. To cope with such environments, IoT systems can be engineered as goal-driven and self-adaptive systems. A goal-driven IoT system is composed of a dynamic set of IoT devices and services that temporarily connect and cooperate to achieve a specific goal. Several approaches have been proposed to engineer goal-driven and self-adaptive IoT systems. However, none of the existing approaches enable goal-driven IoT systems to automatically detect security threats and autonomously adapt to mitigate them. Toward bridging these gaps, this paper proposes a distributed architectural Approach for engineering goal-driven IoT Systems that can autonomously SElf-adapt to secuRity Threats in their environments (ASSERT). ASSERT exploits techniques and adopts notions, such as agents, federated learning, feedback loops, and blockchain, for maintaining the systems' security and enhancing the trustworthiness of the adaptations they perform. The results of the experiments that we conducted to validate the approach's feasibility show that it performs and scales well when detecting security threats, performing autonomous security adaptations to mitigate the threats and enabling systems' constituents to learn about security threats in their environments collaboratively.

Place, publisher, year, edition, pages
MDPI, 2022
Keywords
Internet of Things, blockchain, multi-agent systems, security, self-adaptive and goal-driven systems, software architecture
National Category
Computer Sciences
Identifiers
urn:nbn:se:mau:diva-55176 (URN)10.3390/s22186842 (DOI)000858946100001 ()36146191 (PubMedID)2-s2.0-85138427481 (Scopus ID)
Available from: 2022-10-17 Created: 2022-10-17 Last updated: 2024-02-05Bibliographically approved
Alkhabbas, F., De Sanctis, M., Bucchiarone, A., Cicchetti, A., Spalazzese, R., Davidsson, P. & Iovino, L. (2022). ROUTE: A Framework for Customizable Smart Mobility Planners. In: IEEE 19TH INTERNATIONAL CONFERENCE ON SOFTWARE ARCHITECTURE (ICSA 2022): . Paper presented at 19th IEEE International Conference on Software Architecture (ICSA), MAR 12-15, 2022, Honolulu, HI, USA (pp. 169-179). Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>ROUTE: A Framework for Customizable Smart Mobility Planners
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2022 (English)In: IEEE 19TH INTERNATIONAL CONFERENCE ON SOFTWARE ARCHITECTURE (ICSA 2022), Institute of Electrical and Electronics Engineers (IEEE), 2022, p. 169-179Conference paper, Published paper (Refereed)
Abstract [en]

Multimodal journey planners are used worldwide to support travelers in planning and executing their journeys. Generated travel plans usually involve local mobility service providers, consider some travelers' preferences, and provide travelers information about the routes' current status and expected delays. However, those planners cannot fully consider the special situations of individual cities when providing travel planning services. Specifically, authorities of different cities might define customizable regulations or constraints of movements in the cities (e.g., due to construction works or pandemics). Moreover, with the transformation of traditional cities into smart cities, travel planners could leverage advanced monitoring features. Finally, most planners do not consider relevant information impacting travel plans, for instance, information that might be provided by travelers (e.g., a crowded square) or by mobility service providers (e.g., changing the timetable of a bus). To address the aforementioned shortcomings, in this paper, we propose ROUTE, a framework for customizable smart mobility planners that better serve the needs of travelers, local authorities, and mobility service providers in the dynamic ecosystem of smart cities. ROUTE is composed of an architecture, a process, and a prototype developed to validate the feasibility of the framework. Experiments' results show that the framework scales well in both centralized and distributed deployment settings.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2022
Keywords
Multimodal Journey Planners, Software Framework, Multi-tier Architecture, Smart Mobility
National Category
Software Engineering
Identifiers
urn:nbn:se:mau:diva-55117 (URN)10.1109/ICSA53651.2022.00024 (DOI)000838691200016 ()2-s2.0-85132012974 (Scopus ID)978-1-6654-1728-0 (ISBN)978-1-6654-1729-7 (ISBN)
Conference
19th IEEE International Conference on Software Architecture (ICSA), MAR 12-15, 2022, Honolulu, HI, USA
Available from: 2022-09-23 Created: 2022-09-23 Last updated: 2024-01-11Bibliographically approved
Alkhabbas, F., Spalazzese, R. & Davidsson, P. (2021). Human-Centric Emergent Configurations: Supporting the User Through Self-configuring IoT Systems. In: Hasan Ayaz; Umer Asgher; Lucas Paletta (Ed.), Advances in Neuroergonomics and Cognitive Engineering: Proceedings of the AHFE 2021 Virtual Conferences on Neuroergonomics and Cognitive Engineering, Industrial Cognitive Ergonomics and Engineering Psychology, and Cognitive Computing and Internet of Things, July 25-29, 2021, USA. Paper presented at AHFE 2021 Virtual Conferences on Neuroergonomics and Cognitive Engineering, Industrial Cognitive Ergonomics and Engineering Psychology, and Cognitive Computing and Internet of Things, July 25-29, 2021, USA (pp. 411-418). Springer
Open this publication in new window or tab >>Human-Centric Emergent Configurations: Supporting the User Through Self-configuring IoT Systems
2021 (English)In: Advances in Neuroergonomics and Cognitive Engineering: Proceedings of the AHFE 2021 Virtual Conferences on Neuroergonomics and Cognitive Engineering, Industrial Cognitive Ergonomics and Engineering Psychology, and Cognitive Computing and Internet of Things, July 25-29, 2021, USA / [ed] Hasan Ayaz; Umer Asgher; Lucas Paletta, Springer, 2021, p. 411-418Conference paper, Published paper (Refereed)
Abstract [en]

The Internet of Things (IoT) is revolutionizing our environments with novel types of services and applications by exploiting the large number of diverse connected things. One of the main challenges in the IoT is to engineer systems to support human users to achieve their goals in dynamic and uncertain environments. For instance, the mobility of both users and devices makes it infeasible to always foresee the available things in the users’ current environments. Moreover, users’ activities and/or goals might change suddenly. To support users in such environments, we developed an initial approach that exploits the notion of Emergent Configurations (ECs) and mixed initiative techniques to engineer self-configuring IoT systems. An EC is a goal-driven IoT system composed of a dynamic set of temporarily connecting and cooperating things. ECs are more flexible and usable than IoT systems whose constituents and interfaces are fully specified at design time

Place, publisher, year, edition, pages
Springer, 2021
Series
Lecture Notes in Networks and Systems, ISSN 2367-3370, E-ISSN 2367-3389 ; 259
Keywords
Dynamic generation of user interfaces, Human-centric emergent configurations, Internet of Things
National Category
Information Systems, Social aspects
Identifiers
urn:nbn:se:mau:diva-45120 (URN)10.1007/978-3-030-80285-1_48 (DOI)2-s2.0-85112111445 (Scopus ID)9783030802844 (ISBN)
Conference
AHFE 2021 Virtual Conferences on Neuroergonomics and Cognitive Engineering, Industrial Cognitive Ergonomics and Engineering Psychology, and Cognitive Computing and Internet of Things, July 25-29, 2021, USA
Available from: 2021-08-23 Created: 2021-08-23 Last updated: 2023-12-28Bibliographically approved
Alawadi, S., Mera, D., Fernandez-Delgado, M., Alkhabbas, F., Olsson, C. M. & Davidsson, P. (2020). A comparison of machine learning algorithms for forecasting indoor temperature in smart buildings. Energy Systems, Springer Verlag, 13, 689-705
Open this publication in new window or tab >>A comparison of machine learning algorithms for forecasting indoor temperature in smart buildings
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2020 (English)In: Energy Systems, Springer Verlag, ISSN 1868-3967, E-ISSN 1868-3975, Vol. 13, p. 689-705Article in journal (Refereed) Published
Abstract [en]

The international community has largely recognized that the Earth's climate is changing. Mitigating its global effects requires international actions. The European Union (EU) is leading several initiatives focused on reducing the problems. Specifically, the Climate Action tries to both decrease EU greenhouse gas emissions and improve energy efficiency by reducing the amount of primary energy consumed, and it has pointed to the development of efficient building energy management systems as key. In traditional buildings, households are responsible for continuously monitoring and controlling the installed Heating, Ventilation, and Air Conditioning (HVAC) system. Unnecessary energy consumption might occur due to, for example, forgetting devices turned on, which overwhelms users due to the need to tune the devices manually. Nowadays, smart buildings are automating this process by automatically tuning HVAC systems according to user preferences in order to improve user satisfaction and optimize energy consumption. Towards achieving this goal, in this paper, we compare 36 Machine Learning algorithms that could be used to forecast indoor temperature in a smart building. More specifically, we run experiments using real data to compare their accuracy in terms of R-coefficient and Root Mean Squared Error and their performance in terms of Friedman rank. The results reveal that the ExtraTrees regressor has obtained the highest average accuracy (0.97%) and performance (0,058%) over all horizons.

Place, publisher, year, edition, pages
Springer, 2020
National Category
Energy Systems
Identifiers
urn:nbn:se:mau:diva-13827 (URN)10.1007/s12667-020-00376-x (DOI)000509132000001 ()2-s2.0-85078337875 (Scopus ID)
Available from: 2020-03-24 Created: 2020-03-24 Last updated: 2024-02-05Bibliographically approved
Alkhabbas, F., Murturi, I., Spalazzese, R., Davidsson, P. & Dustdar, S. (2020). A Goal driven Approach for Deploying Self-adaptive IoT Systems. In: Lisa O’Conner (Ed.), Proceedings: 2020 IEEE International Conference on Software Architecture (ICSA), Salvador, Brazil, 16-20 March 2020. Paper presented at IEEE International Conference on Software Architecture (ICSA), Salvador, Brazil, 16-20 March 2020 (pp. 146-156).
Open this publication in new window or tab >>A Goal driven Approach for Deploying Self-adaptive IoT Systems
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2020 (English)In: Proceedings: 2020 IEEE International Conference on Software Architecture (ICSA), Salvador, Brazil, 16-20 March 2020 / [ed] Lisa O’Conner, 2020, p. 146-156Conference paper, Published paper (Refereed)
Abstract [en]

Engineering Internet of Things (IoT) systems is a challenging task partly due to the dynamicity and uncertainty of the environment including the involvement of the human in the loop. Users should be able to achieve their goals seamlessly in different environments, and IoT systems should be able to cope with dynamic changes. Several approaches have been proposed to enable the automated formation, enactment, and self-adaptation of goal-driven IoT systems. However, they do not address deployment issues. In this paper, we propose a goal-driven approach for deploying self-adaptive IoT systems in the Edge-Cloud continuum. Our approach supports the systems to cope with the dynamicity and uncertainty of the environment including changes in their deployment topologies, i.e., the deployment nodes and their interconnections. We describe the architecture and processes of the approach and the simulations that we conducted to validate its feasibility. The results of the simulations show that the approach scales well when generating and adapting the deployment topologies of goal-driven IoT systems in smart homes and smart buildings.

National Category
Information Systems, Social aspects
Identifiers
urn:nbn:se:mau:diva-36984 (URN)10.1109/ICSA47634.2020.00022 (DOI)000584237000014 ()2-s2.0-85085928360 (Scopus ID)978-1-7281-4659-1 (ISBN)978-1-7281-4660-7 (ISBN)
Conference
IEEE International Conference on Software Architecture (ICSA), Salvador, Brazil, 16-20 March 2020
Available from: 2020-11-26 Created: 2020-11-26 Last updated: 2024-02-05Bibliographically approved
Alkhabbas, F., Alawadi, S., Spalazzese, R. & Davidsson, P. (2020). Activity Recognition and User Preference Learning for Automated Configuration of IoT Environments. In: IoT '20: Proceedings of the 10th International Conference on the Internet of Things. Paper presented at IoT '20: 10th International Conference on the Internet of Things, Malmö Sweden 6-9 October, 2020 (pp. 1-8). New York, United States: ACM Digital Library, Article ID 3.
Open this publication in new window or tab >>Activity Recognition and User Preference Learning for Automated Configuration of IoT Environments
2020 (English)In: IoT '20: Proceedings of the 10th International Conference on the Internet of Things, New York, United States: ACM Digital Library, 2020, p. 1-8, article id 3Conference paper, Published paper (Refereed)
Abstract [en]

Internet of Things (IoT) environments encompass different types of devices and objects that offer a wide range of services. The dynamicity and uncertainty of those environments, including the mobility of users and devices, make it hard to foresee at design time available devices, objects, and services. For the users to benefit from such environments, they should be proposed services that are relevant to the specific context and can be provided by available things. Moreover, environments should be configured automatically based on users' preferences. To address these challenges, we propose an approach that leverages Artificial Intelligence techniques to recognize users' activities and provides relevant services to support users to perform their activities. Moreover, our approach learns users' preferences and configures their environments accordingly by dynamically forming, enacting, and adapting goal-driven IoT systems. In this paper, we present a conceptual model, a multi-tier architecture, and processes of our approach. Moreover, we report about how we validated the feasibility and evaluated the scalability of the approach through a prototype that we developed and used.

Place, publisher, year, edition, pages
New York, United States: ACM Digital Library, 2020
National Category
Information Systems, Social aspects
Identifiers
urn:nbn:se:mau:diva-36986 (URN)10.1145/3410992.3411003 (DOI)2-s2.0-85123041965 (Scopus ID)978-1-4503-8758-3 (ISBN)
Conference
IoT '20: 10th International Conference on the Internet of Things, Malmö Sweden 6-9 October, 2020
Available from: 2020-11-26 Created: 2020-11-26 Last updated: 2024-02-05Bibliographically approved
Alkhabbas, F., Spalazzese, R. & Davidsson, P. (2020). An Agent-based Approach to Realize Emergent Configurationsin the Internet of Things. Electronics, 9(9), Article ID 1347.
Open this publication in new window or tab >>An Agent-based Approach to Realize Emergent Configurationsin the Internet of Things
2020 (English)In: Electronics, E-ISSN 2079-9292, Vol. 9, no 9, article id 1347Article in journal (Refereed) Published
Abstract [en]

The Internet of Things (IoT) has enabled physical objects and devices, often referred to as things, to connect and communicate. This has opened up for the development of novel types of services that improve the quality of our daily lives. The dynamicity and uncertainty of IoT environments, including the mobility of users and devices, make it hard to foresee at design time available things and services. Further, users should be able to achieve their goals seamlessly in arbitrary environments. To address these challenges, we exploit Artificial Intelligence (AI) to engineer smart IoT systems that can achieve user goals and cope with the dynamicity and uncertainty of their environments. More specifically, the main contribution of this paper is an approach that leverages the notion of Belief-Desire-Intention agents and Machine Learning (ML) techniques to realize Emergent Configurations (ECs) in the IoT. An EC is an IoT system composed of a dynamic set of things that connect and cooperate temporarily to achieve a user goal. The approach enables the distributed formation, enactment, adaptation of ECs, and conflict resolution among them. We present a conceptual model of the entities of the approach, its underlying processes, and the guidelines for using it. Moreover, we report about the simulations conducted to validate the feasibility of the approach and evaluate its scalability. View Full-Text

Place, publisher, year, edition, pages
MDPI, 2020
Keywords
emergent configurations; artificial intelligence; self-adaptive IoT systems
National Category
Information Systems, Social aspects
Identifiers
urn:nbn:se:mau:diva-36985 (URN)10.3390/electronics9091347 (DOI)000580061200001 ()2-s2.0-85089677698 (Scopus ID)
Available from: 2020-11-26 Created: 2020-11-26 Last updated: 2024-02-05Bibliographically approved
Alkhabbas, F., Spalazzese, R., Cerioli, M., Leotta, M. & Reggio, G. (2020). On the Deployment of IoT Systems: An Industrial Survey. In: 2020 IEEE International Conference on Software Architecture Companion (ICSA-C): . Paper presented at 2020 IEEE International Conference on Software Architecture Companion (ICSA-C), 16-20 March 2020, Salvador, Brazil.
Open this publication in new window or tab >>On the Deployment of IoT Systems: An Industrial Survey
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2020 (English)In: 2020 IEEE International Conference on Software Architecture Companion (ICSA-C), 2020Conference paper, Published paper (Refereed)
Abstract [en]

Internet of Things (IoT) systems are complex and multifaceted, and the design of their architectures needs to consider many aspects at a time. Design decisions concern, for instance, the modeling of software components and their interconnections, as well as where to deploy the components within the available hardware infrastructure in the Edge-Cloud continuum. A relevant and challenging task, in this context, is to identify optimal deployment models due to all the different aspects involved, such as extra-functional requirements of the system, heterogeneity of the hardware resources concerning their processing and storage capabilities, and constraints like legal issues and operational cost limits. To gain insights about the deployment decisions concerning IoT systems in practice, and the factors that influence those decisions, we report about an industrial survey we conducted with 66 IoT architects from 18 countries across the world. Each participant filled in a questionnaire that comprises 15 questions. By analyzing the collected data, we have two main findings: (i) architects rely on the Cloud more than the Edge for deploying the software components of IoT systems, in the majority of the IoT application domains; and (ii) the main factors driving deployment decisions are four: reliability, performance, security, and cost.

National Category
Information Systems, Social aspects
Identifiers
urn:nbn:se:mau:diva-36983 (URN)10.1109/ICSA-C50368.2020.00012 (DOI)000587897600006 ()2-s2.0-85085747272 (Scopus ID)978-1-7281-7415-0 (ISBN)978-1-7281-7416-7 (ISBN)
Conference
2020 IEEE International Conference on Software Architecture Companion (ICSA-C), 16-20 March 2020, Salvador, Brazil
Available from: 2020-11-26 Created: 2020-11-26 Last updated: 2024-02-05Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-8025-4734

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